R中2个观测值的线性回归

Question

我试图根据两个观察结果做一个简单的回归：

> x=c(1,2)
> y=c(3,5)
> fit <- lm(y ~ x)
> Prediction <- predict(fit, newdata=c(3,4))
Error in eval(predvars, data, env) : 
  numeric 'envir' arg not of length one
> summary(fit)

Call:
lm(formula = y ~ x)

Residuals:
ALL 2 residuals are 0: no residual degrees of freedom!

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)        1         NA      NA       NA
x                  2         NA      NA       NA

Residual standard error: NaN on 0 degrees of freedom
Multiple R-squared:      1, Adjusted R-squared:    NaN 
F-statistic:   NaN on 1 and 0 DF,  p-value: NA

我知道我不应该在我的模型中得到任何残差，但为什么我不能预测x的未来值？

Answer 1

我认为newdata需要采用list()形式。

predict(fit, newdata=list(x=c(3,4)))